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Professorship for Information Systems, in particular Machine Learning

Organisational unit: Professoship

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Main research areas

Research

We are interested in statistical machine learning with a focus on spatiotemporal problems, such as user navigation on the web, adaptive testing and adaptive learning environments, and the coordination of football players on the pitch. While we mainly focus on basic research, we also collaborate with selected partners in academia, sports and industry in different projects.

Teaching

Our teaching focuses on introductory/advanced machine learning and data mining as well as basic statistics. We regularly offer courses in the Management & Data Science Master and the Information Systems Bachelor programs. Exemplary courses comprise Deep Learning (Data Science), Statistics (Information Systems), and Machine Learning & Data Mining (Engineering).

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  1. 2019
  2. Published

    Frame-based Optimal Design

    Mair, S., Rudolph, Y., Closius, V. & Brefeld, U., 23.01.2019, Machine learning and knowledge discovery in databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham: Springer Nature AG, Vol. 2. p. 447-463 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11052 LNAI).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  3. Published

    Reformstudie Belgien: eine Effektstudie zur Einführung von kompetenzorientiertem Rahmenplan und mBook

    Schreiber, W., Trautwein, U., Wagner, W. & Brefeld, U., 01.02.2019, Geschichtsdidaktischer Zwischenhalt: Beiträge aus der Tagung "Kompetent machen für ein Leben in, mit und durch Geschichte" in Eichstätt vom November 2017. Schreiber, W., Ziegler, B. & Kühberger, C. (eds.). 1. ed. Münster: Waxmann Verlag, p. 161-174 14 p. 2

    Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research

  4. Published

    Learning to Rate Player Positioning in Soccer

    Dick, U. & Brefeld, U., 01.03.2019, In: Big Data. 7, 1, p. 71-82 12 p.

    Research output: Journal contributions › Journal articles › Research › peer-review

  5. Published

    Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

    Brefeld, U. (Editor), Davis, J. (Editor), Van Haaren, J. (Editor) & Zimmermann, A. (Editor), 05.04.2019, Springer Nature AG. 179 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11330 LNAI)

    Research output: Books and anthologies › Collected editions and anthologies › Research

  6. Published

    Predicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language Tutoring

    Pandarova, I., Schmidt, T., Hartig, J., Boubekki, A., Jones, R. D. & Brefeld, U., 15.08.2019, In: International Journal of Artificial Intelligence in Education. 29, 3, p. 342-367 26 p.

    Research output: Journal contributions › Journal articles › Research › peer-review

  7. Published

    Personalized Transaction Kernels for Recommendation Using MCTS

    Tavakol, M., Joppen, T., Brefeld, U. & Fürnkranz, J., 01.09.2019, KI 2019: Advances in Artificial Intelligence - 42nd German Conference on AI, Proceedings. Benzmüller, C. & Stuckenschmidt, H. (eds.). Wiesbaden: Springer, p. 338-352 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11793 LNAI).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  8. Published

    Zur empirischen Beforschung des mBooks Belgien: Die Chancen eines Methodenmix

    Schreiber, W., Wagner, W., Trautwein, U. & Brefeld, U., 10.2019, Das Geschichtsschulbuch: Lehren – Lernen – Forschen . Kühberger, C., Bernhard, R. & Bramann, C. (eds.). Münster: Waxmann Verlag, p. 57-80 24 p. (Salzburger Beiträge zur Lehrer/innen/bildung; vol. 6).

    Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

  9. 2020
  10. Published

    Assessing User Behavior by Mouse Movements

    Matthiesen, J. J. & Brefeld, U., 2020, HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. Stephanidis, C. & Antona, M. (eds.). Cham: Springer, p. 68-75 8 p. (Communications in Computer and Information Science; vol. 1224 CCIS).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  11. Published

    Coresets for Archetypal Analysis

    Mair, S. & Brefeld, U., 2020, 32rd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019. Wallach, H. & Larochelle, H. (eds.). Red Hook: Curran Associates, Vol. 10. p. 7215-7223 9 p. (Advances in neural information processing systems; vol. 32).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  12. Published

    Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?

    Rudolph, Y., Brefeld, U. & Dick, U., 2020, In: Proceedings of Machine Learning Research. 137, p. 136-147 12 p.

    Research output: Journal contributions › Conference article in journal › Research › peer-review

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